2008 AFAR Research Grant: Statistical Methods for Genetical Transcriptome Studies of Aging

Please give a brief summary of your AFAR research project.
This project aims to develop statistical and computational methods to identify genetic loci related to aging and elucidate mechanisms of these loci controlling downstream genes and biological pathways. We will utilize the high throughput expression data and genotype data to perform genetic association study for age specific genes and to investigate the age-related rewiring of co-expression network. The results will help us to understand the biological mechanisms of aging which will shed light on prognosis and treatment of aging-related disabilities and diseases.

What problems are you addressing and what specific questions will your research seek to answer?
Aging is one of the most complicated biological processes that might involve thousands of genetic and non-genetic components. There is great interest to clarify to what extent lifespan variation can be attributed to genetic variation and what specific roles these genetic components play in aging. Specifically, we are trying to answer: how to develop efficient and rational statistical methods for whole genome association studies which use gene expressions as intermediate phenotypes; how to identify age-related rewiring of co-expression network; how to identify genetic components of age-specific change of transcriptome.

What aspects of your project are most interesting from a scientific point of view?
We are trying to develop efficient model selection method with sound false positive control procedure to perform genome-wide association study for age-related genes. This model selection will focus on marker selection rather than prediction accuracy and it will take the false discovery control into account. The investigation of age-related rewiring of co-expression network is an application of network analysis where the relationships among biological systems deteriorate as a function of age. We will focus on developing formal statistical inference about the significance of network change. In addition to identifying genetic component for single gene, we are also interested in identifying markers that have only a moderate or weak effect on every gene but may have a significant impact on the whole aging-related pathway or function module.

What are the implications of your research for age-related diseases and disorders?
Understanding the genetics of aging can provide prevention and treatment targets for aging-related diseases and disorders. Looking at the genetic components of the perturbed co-expression networks may give us additional information about aging mechanisms and provide candidates that have the potential to partially restore the functional decay in aging.

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